中文摘要：

首先对洞庭湖大桥处的自然脉动风进行了小波分析，从分析结果可以看出．自然脉动风具有一定的间歇性和局部相似性。传统的谐波合成法（WAWS）和线性滤波器方法（ARMA）虽然可以模拟随机风场的脉动风，但是它们无法模拟脉动风的局部相似性和间歇性。针对这一点，采用Meyer小波基，利用小波逆变换，模拟随机风场的脉动风。最后，根据目标谱，模拟了随机风场的脉动风，模拟的脉动风具有和自然脉动风类似的间歇性和局部相似性，同时模拟脉动风的风谱与目标风谱基本吻合，说明了论文方法的有效性。

英文摘要：

The wavelet transform is applied to the time history analysis on a set of wind velocity data measured on the Dongting Lake Bridge, through which, the self-similarity and intermittency of the turbulence are indicated. Although the conventional methods such as WAWS and ARMA can be used to simulate stochastic wind fields, they cannot find the results as the self-similarity and intermittency of turbulence. Under the above premises, in this paper the Meyer wavelet base and then the inverse wavelet transform are employed to simulate the stochastic wind field. Finally, according to the target power spectrum, the result of the simulation of the stochastic wind field is given, which shows that for the simulated wind velocity fluctuation data, the properties as self-similarity and intermittency of turbulence match the ones of the measured data. The power spectrum of the generated time history is identical with that of the measured time history. It proves that the method presented in this paper is effectual.